Multidimensional arrays with semantics in JavaScript.

xndarray works on browsers and any tool following the CommonJS/node module conventions.

A minified browser version of this library is available in the GitHub releases as well as on the jsDelivr CDN. It can be included like that:

<script src="//cdn.jsdelivr.net/xndarray/0.3/xndarray.min.js"></script>
<script>
var arr = xndarray(...)
</script>

If you use xndarray within a CommonJS/node environment, then import the constructor as follows:

var xndarray = require('xndarray')

When using the minified browser version, then this constructor is made available globally under the same name.

• data is a 1D array storage. It is either an instance of Array, a typed array, or an object that implements get(), set(), .length
• shape is the shape of the view as an array of integers (Default: [data.length])
• names is an array of dimension names (Default: ['dim_0','dim_1',...])
• coords is a coordinates map of 1D array storages. Each key is a (dimension) name and each value is either an instance of Array, a typed array, an ndarray, or an object that implements get(), set(), .length (Default: {dim_0: [0,1,2,...], dim_1: [0,1,2,...],...})
• stride is the resulting stride of the view. (Default: row major)
• offset is the offset to start the view (Default: 0)

var arr = xndarray([1,2,3,4,5,6], {
  shape: [2,3],
  names: ['y','x'],
  coords: {
    y: [10,12,14],
    x: [100,101,102],
    t: [new Date('2001-01-01')]
  }
})

// arr == 1 2 3
//        4 5 6

In the example, there are coordinates for the y and x dimensions plus an extra coordinate named t. Extra coordinates are ignored in operations like slicing and carried over unchanged.

You can construct 0D arrays by defining an empty shape without dimension names:

var arr = xndarray([5], {shape: [], coords: {time: [new Date('2001-01-01')]})

This constructor variant wraps existing ndarray objects.

• ndarr is an ndarray object.
• names is an array of dimension names (Default: ['dim_0','dim_1',...])
• coords is a coordinates map of 1D array storages. Each key is a (dimension) name and each value is either an instance of Array, a typed array, an ndarray, or an object that implements get(), set(), .length (Default: {dim_0: [0,1,2,...], dim_1: [0,1,2,...],...})

xndarray is fully compatible with ndarray and can directly wrap such objects:

var nd = ndarray([1,2,3,4], [2,2])
var xnd = xndarray(nd, {
  names: ['y','x'],
  coords: {
    y: [10,12,14],
    x: [100,101,102],
    t: [new Date('2001-01-01')]
  }
})

All ndarray modules can directly be used on xndarray objects:

var unpack = require('ndarray-unpack')
var nd2 = unpack(xnd) // [[1,2],[3,4]]

ndarray functions that return a new ndarray object will not have any xndarray functionality and have to be wrapped again.

Members originating from ndarray:

• array.data - The underlying 1D storage for the multidimensional array
• array.shape - The shape of the array
• array.dimension - Dimension of the array as an integer (equals array.shape.length)
• array.size - Size of the array in logical elements (equals array.shape[0]*array.shape[1]*...)
• array.stride - The layout of the array in memory
• array.offset - The starting offset of the array in memory
• array.dtype - String representing the underlying data type
• array.order - Order of the stride of the array, sorted in ascending length

Additional members:

• array.names - The dimension names. A string array of length array.dimension.
• array.coords - The coordinates. A Map from (dimension) name to 1D ndarrays.

var arr = xndarray([1,2,3,4,5,6], {shape: [2,3], names: ['y','x']})

// arr.get(0, 1)
var v = arr.xget({y: 0, x: 1}) 

// v == 2

var arr = xndarray([1,2,3,4,5,6], {shape: [2,3], names: ['y','x']})

// arr.set(1, 1, 8)
arr.xset({y: 1, x: 1}, 8)

// arr == 1 2 3
//        4 8 6

var arr = xndarray([1,2,3,4,5,6], {shape: [2,3], names: ['y','x']})

// arr.index(1, 0)
var idx = arr.xindex({y: 1, x: 0})

// idx == 3

var arr = xndarray([1,2,3,4,5,6], {
  shape: [2,3],
  names: ['y','x'],
  coords: {
    y: [10,12,14],
    x: [100,101,102]
  }
})

// arr == 1 2 3
//        4 5 6

// arr.lo(null, 1)
var a = arr.xlo({x: 1})

// a == 2 3
//      5 6
// a.coords.get('y') == 10 12 14
// a.coords.get('x') == 101 102

var arr = xndarray([1,2,3,4,5,6], {
  shape: [2,3],
  names: ['y','x'],
  coords: {
    y: [10,12,14],
    x: [100,101,102]
  }
})

// arr.hi(null, 2)
var a = arr.xhi({x: 2})

// a == 1 2
//      4 5
// a.coords.get('y') == 10 12 14
// a.coords.get('x') == 100 101

var arr = xndarray([1,2,3,4,5,6], {
  shape: [2,3],
  names: ['y','x'],
  coords: {
    y: [10,12,14],
    x: [100,101,102]
  }
})

// arr.step(null, 2)
var a = arr.xstep({x: 2})

// a == 1 3
//      4 6
// a.coords.get('y') == 10 12 14
// a.coords.get('x') == 100 102

The transpose/xtranspose functions change the axis order. This has no relevance if you only work with x-prefixed functions since they work directly on axis names.

var arr = xndarray([1,2,3,4,5,6], {shape: [2,3], names: ['y','x']})

// arr.transpose(1, 0)
var a = arr.xtranspose('x', 'y')

// a == 1 4
//      2 5
//      3 6
// 
// a.names == ['x','y']

var arr = xndarray([1,2,3,4,5,6], {
  shape: [2,3],
  names: ['y','x'],
  coords: {
    y: [10,12,14],
    x: [100,101,102]
  }
})

// arr.pick(null, 1)
var a = arr.xpick({x: 1})

// a == 2 5
// a.dimension == 1
// a.names == ['y']
// a.coords.get('y') == 10 12 14
// a.coords.get('x') == 101

Note that the x coordinates get reduced to a single value in the example.

This library is inspired by the Python packages PyHRF (see pyhrf.ndarray.xndarray class) and xarray. It is based on and compatible with the ndarray JavaScript library.